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👋 Hi , I'm Ritesh


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"In God we trust. All others must bring data."

Currently, I'm an AI Engineer deepening my knowledge in LLM frameworks like LangChain, LlamaIndex, vector databases, RAG, evaluating RAG based applications using various frameworks and developing LLM backend infrastructure using FastAPI for Next JS projects. I'm also exploring Azure AI services like Azure OpenAI, Search, Document Intelligence, and Copilot.

My journey in AI and data began with a Master's in Applied Artificial Intelligence from Stevens Institute of Technology. I'm passionate about turning complex data into practical solutions that positively impact society.

Teaching and research roles at Stevens Institute for Artificial Intelligence have refined my technical and communication skills, allowing me to simplify complex concepts for diverse teams.

I'm excited by the potential of AI, machine learning, and cloud technologies, and I'm actively broadening my knowledge in these areas. My technical expertise includes Python, deep learning, full-stack development, with practical skills in SQL, HTML, CSS, JavaScript, and PHP. I've worked with AWS, Azure, Linux, Hadoop, and PySpark, and I'm committed to staying current with technology trends and practical applications.

🛠️ Languages and Tools :


🤖 Data & ML :

Python NumPy Pandas Scikitlearn Tensorflow Pytorch Keras Selenium Tableau Powerbi

☁️ Cloud :

AWS GCP Firebase Azure

💾 Databases :

PostgreSQL Mysql SQLite Snowflake

🌐 Web Dev :

HTML5 CSS3 Typescript Javascript Tailwind BootStrap React Nodejs Django Next Fastapi

🔨 Tools :

Linux Docker Terraform Git GitLab Jira Bitbucket



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Ritesh Panditi's Projects

aws-mlu-explain icon aws-mlu-explain

Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/

codesearchnet icon codesearchnet

Datasets, tools, and benchmarks for representation learning of code.

deep-learning_neural-nets-628 icon deep-learning_neural-nets-628

This repo consists of the content taught in AAI 628: Data Acquisition and Processing II (Deep Learning) taught in Spring 2022

eeg-synthetic-data-using-gans icon eeg-synthetic-data-using-gans

This repo is for the submission for my Final Year Project on creating Synthetic EEG Data using General Adverserial Neural Networks (GANs) in order to augment existing training datasets to reduce caliberation time in MI-based BCI's.

fsdl-text-recognizer-2022-labs icon fsdl-text-recognizer-2022-labs

Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022

lnn icon lnn

A `Neural = Symbolic` framework for sound and complete weighted real-value logic

made-with-ml icon made-with-ml

Learn how to responsibly develop, deploy and maintain production machine learning applications.

ml-fastvit icon ml-fastvit

This repository contains the official implementation of the research paper, "FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization"

music-recommendation-system icon music-recommendation-system

The final project for AAI 627: Data Acquisition, Modeling and Analysis: Big Data whilst pursuing a Master's in Applied Artificial Intelligence.

shift_comp_demo icon shift_comp_demo

Contains the submission from a sample competitor in the SHIFT Algorithmic Trading Competition.

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